Search: “local-ai”

Based on the available search results, I cannot locate specific details about the b8989 release. However, b8989 is a commit hash from the llama.cpp repository releases. llama.cpp is a C/C++ implementa

llama.cpp b8990 is a release version of a C/C++ LLM inference tool from the ggml-org project. The release likely contains bug fixes, performance improvements, or new features for local language model

llama.cpp is a C/C++ implementation for LLM inference , and b8991 is a specific release version from the project's ongoing development cycle. The search results indicate that the project doesn't follo

b8992 is a build release from the llama.cpp project, which publishes multiple releases in a single day . llama.cpp enables LLM inference with minimal setup and state-of-the-art performance on a wide r

ComfyUI is often faster on macOS than AUTOMATIC1111, while Forge offers improvements in speed over A1111 with memory-efficient attention support . SwarmUI features a modular interface with support for

A blind realism test comparing Flux.2 Klein 9B with Z-Image Turbo, where Klein 9B showed better prompt adherence and natural composition . Z-Image Turbo generally won on realism, cinematic quality, an

arXiv:2603.02854v2 Announce Type: replace-cross Abstract: Existing language-conditioned navigation systems typically rely on modular pipelines or trajectory generators, but the latter use each scene--

ComfyUI Video Combine Plus is a tool for transforming sequences of images into professional-quality videos with flexibility in formats, frame rates, and looping options. The node merges images or late

arXiv:2604.26095v1 Announce Type: new Abstract: {Closed-loop inverse source localization and characterization (ISLC) requires a mobile agent to select measurements that localize sources and infer late

arXiv:2602.19179v2 Announce Type: replace Abstract: Gaussian inference on smooth manifolds is central to robotics, but exact marginalization and conditioning are generally non-Gaussian and geometry-de

arXiv:2604.26557v1 Announce Type: cross Abstract: The increasing deployment of Large Language Model (LLM) inference on edge AI systems demands efficient execution under tight memory budgets. A key cha

arXiv:2604.26857v1 Announce Type: new Abstract: Deploying accurate object detection for Vulnerable Road User (VRU) safety on edge hardware requires balancing model capacity against computational const

arXiv:2512.18365v2 Announce Type: replace Abstract: Diffusion models have emerged as powerful priors for image editing tasks such as inpainting and local modification, where the objective is to genera

arXiv:2510.05174v4 Announce Type: replace-cross Abstract: When are multi-agent LLM systems merely a collection of individual agents versus an integrated collective with higher-order structure? We intr

arXiv:2604.25949v1 Announce Type: new Abstract: Reliable perception for robotics depends on large-scale labeled data, yet real-world datasets rely on heavy manual annotation and are time-consuming to

arXiv:2604.26470v1 Announce Type: new Abstract: Industrial systems increasingly depend on Machine Learning (ML), and operate on heterogeneous nodes that must satisfy tight latency, energy, and memory

arXiv:2601.03654v2 Announce Type: replace Abstract: In this study, we introduce a quantum computing method that incorporates Ridglet transforms into quantum processing pipelines for financial time-ser

Manus, an AI company Meta acquired for $2 billion last year is running ads promising quick, easy money with AI: Find local businesses without websites or with bad websites, have AI build them one, the

arXiv:2604.26261v1 Announce Type: new Abstract: Zero-shot 3D Visual Grounding (3DVG) is a critical capability for open-world embodied AI. However, existing methods are fundamentally bottlenecked by th

This Reddit thread likely discusses hardware recommendations and considerations for purchasing a new laptop capable of running Ollama, a tool that enables running large language models locally. The di

arXiv:2604.26472v1 Announce Type: cross Abstract: We study sequential interventions under prerequisite constraints. In this setting, admissible intervention sequences are paths in the ideal lattice of

arXiv:2603.05959v3 Announce Type: replace Abstract: Reconstructing 3D geometry from streaming video requires continuous inference under bounded resources. Recent geometric foundation models achieve im

Pi + @huggingface llamacpp + Qwen3.6 = 🔥🔥🔥🔥 turns out not killing the prefix cache all the time and notnhaving a humongous set of tools and a massive system prompt is good for local model use. who'd h

arXiv:2604.26318v1 Announce Type: new Abstract: Point cloud registration (PCR) is a fundamental task for integrating 3D observations in remote sensing applications. This paper proposes a fast and effe

arXiv:2604.26073v1 Announce Type: cross Abstract: Industrial chemical plants often operate under strict data confidentiality constraints, making centralized data-driven process modeling difficult. Fed

arXiv:2604.17612v2 Announce Type: replace-cross Abstract: Multi-agent systems built on large language models (LLMs) are difficult to reason about. Coordination errors such as deadlocks or type-mismatc

arXiv:2604.25936v1 Announce Type: cross Abstract: Implicit neural representations are powerful for geometric modeling, but their practical use is often limited by the high computational cost of networ

arXiv:2604.26394v1 Announce Type: cross Abstract: Recent advances in large language models and agentic frameworks have enabled virtual customer assistants (VCAs) for complex support. We present SecMat

arXiv:2604.26940v1 Announce Type: new Abstract: Small language models (SLMs) offer computational efficiency for scalable deployment, yet they often fall short of the reasoning power exhibited by their

arXiv:2604.26897v1 Announce Type: new Abstract: Origami-inspired robotic grippers have shown promising potential for object manipulation tasks due to their compact volume and mechanical flexibility. H

arXiv:2511.20032v3 Announce Type: replace Abstract: Visual attention serves as the primary mechanism through which MLLMs interpret visual information; however, its limited localization capability ofte

arXiv:2604.26553v1 Announce Type: cross Abstract: Large language models (LLMs) demonstrate strong multilingual capabilities, yet often fail to consistently generate responses in the intended language,

arXiv:2604.26837v1 Announce Type: new Abstract: Long-context LLM serving is bottlenecked by the cost of attending over ever-growing KV caches. Dynamic sparse attention promises relief by accessing onl

v0.22.1-rc1 is a pre-release version of Ollama that includes improvements to MLX sampler batching, tokenizer BPE offset handling, NVIDIA TensorRT Model Optimizer support, and fixes for desktop app sta

arXiv:2604.26806v1 Announce Type: cross Abstract: Transformer-based architectures have established a dominant paradigm in global semantic perception; however, they remain fundamentally constrained by

A community repository of AI agent configurations for Ollama has reached 888 GitHub stars, featuring pre-built setups and configurations for running AI agents locally. The project appears to focus on

This discussion covers training custom video LoRAs for Wan and LTX Video models using Low-Rank Adaptation, a fine-tuning technique that customizes outputs for specific subjects, styles, or movements w

arXiv:2604.26604v1 Announce Type: new Abstract: Federated learning (FL) trains a shared model from updates contributed by distributed clients, often implicitly assuming that contributing clients are r

b8969 is a release build of llama.cpp (commit bdc9c74), published on April 29, 2026. Llama.cpp is a C/C++ implementation designed to enable LLM inference with minimal setup and state-of-the-art perfor

b8970 is a release of llama.cpp, a C/C++ project for large language model inference. The naming convention using a build hash (b8970) is typical of llama.cpp's continuous release pattern rather than t

b8971 is a build release of llama.cpp, an open-source C/C++ project for LLM inference . As a numbered build identifier from the llama.cpp repository, this release likely contains bug fixes, performanc

b8972 is a release of llama.cpp, a C/C++ implementation for LLM inference . The release identifier follows llama.cpp's development versioning scheme with frequent builds published to the GitHub releas

b8973 is a release of llama.cpp that added SVE tuned code for the gemm_q8_0_4x8_q8_0() kernel and changed arrays to static const in repack.cpp . The llama.cpp project enables LLM inference with minima

b8978 is a release of llama.cpp, a project designed to enable LLM inference with minimal setup and state-of-the-art performance on a wide range of hardware. The llama.cpp project uses sequential build

B8979 is a llama.cpp release that added SVE (Scalable Vector Extension) tuned code for the gemm_q8_0_4x8_q8_0() kernel and made static const changes to repack.cpp . The release includes pre-built bina

b8981 is a release version of llama.cpp, a C/C++ implementation for LLM inference . Build versions in llama.cpp releases typically contain updates to the underlying ggml library, performance optimizat